Device for non-invasive detection of skin problems associated with diabetes mellitus

ABSTRACT

A medical diagnostic apparatus includes a controller; a user interface; a platform having a horizontal surface; and at least one visible light image sensor positioned below the horizontal surface that is capable of producing a diagnostic visible light image of a bottom portion of a foot or feet positioned on the horizontal surface. At least a portion of the horizontal surface is transparent to visible light. The apparatus may further include at least one infrared image sensor positioned below the horizontal surface that is capable of producing a thermal image of the first target area. The apparatus may further include sensors positioned above the platform capable of producing diagnostic visible light images or thermal images of a top portion of the user&#39;s foot or feet. The apparatus may further include a weight measurement system coupled to the platform.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a division of U.S. patent application Ser. No.16/044248, filed Jul. 24, 2018, which claims the benefit of U.S.Provisional Application No. 62/536388, filed Jul. 24, 2017, the entiredisclosure of which is hereby incorporated by reference herein for allpurposes.

SUMMARY

This summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This summary is not intended to identify key features ofthe claimed subject matter, nor is it intended to be used as an aid indetermining the scope of the claimed subject matter.

In one aspect, a medical diagnostic apparatus includes a controller; auser interface configured for user interaction with the medicaldiagnostic apparatus; a platform having a horizontal surface; a weightmeasurement system coupled to the platform; and at least one visiblelight image sensor positioned below the horizontal surface that iscapable of producing a diagnostic visible light image of a bottomportion of a foot or feet positioned on the horizontal surface. At leasta portion of the horizontal surface is transparent to visible light.

In an embodiment, at least a portion of the horizontal surface istransparent to infrared light suitable for thermal imaging, and theapparatus further includes at least one infrared image sensor positionedbelow the horizontal surface that is capable of producing a thermalimage of the first target area.

In an embodiment, the apparatus further includes at least one visiblelight image sensor positioned above the platform capable of producing adiagnostic visible light image of a top portion of the user's foot orfeet.

In an embodiment, the apparatus further includes at least one infraredimage sensor positioned above the platform capable of producing athermal image of a top portion of the user's foot or feet.

In another aspect, a medical diagnostic apparatus includes a platformhaving a horizontal surface; at least one upper image sensor positionedabove the horizontal surface and configured to capture one or moreimages of a top portion of a foot or feet; at least one lower imagesensor positioned below the horizontal surface and configured to captureone or more images of a bottom portion of the foot or feet; acontroller; and a user interface configured for user interaction withthe medical diagnostic apparatus. At least a portion of the horizontalsurface is transparent to visible light. In an embodiment, two camerasarea are positioned below the horizontal surface. In an embodiment, atleast a portion of the horizontal surface is transparent to infraredlight suitable for thermal imaging, and the medical diagnostic apparatusfurther includes at least one infrared image sensor positioned below thehorizontal surface that is capable of producing a thermal image of thebottom portion of the foot or feet.

In any of the described embodiments, a medical diagnostic apparatus mayinclude a device for testing for peripheral neuropathy. The device mayinclude a controller; a foot platform having at least one opening; atleast one vertically oriented monofilament positioned to pass throughthe at least one opening of the foot platform; and at least one actuatorpositioned below the at least one opening of the foot platform. The atleast one actuator is mechanically coupled to the at least onevertically oriented monofilament and is configured to move the at leastone vertically oriented monofilament to pass through the at least oneopening of the foot platform.

In any of the described embodiments, a medical diagnostic apparatus mayinclude a visual or tactile guide for foot positioning, one or moreillumination sources, or a combination of these or other additionalfeatures.

In another aspect, a computer-implemented method is described forautomated diagnosis of a diabetic foot condition. The method includescapturing, by one or image capture devices of a medical diagnosticapparatus, optical image data of a target area of a foot; collecting, bya touch sensitivity testing device (e.g., a servo-actuated monofilamentprobe) of the medical diagnostic apparatus, physical touch sensitivitydata for the target area of the foot; transmitting, by the medicaldiagnostic apparatus, the optical image data, the physical touchsensitivity data, or a combination of such data to an analysis engine;and outputting, by the analysis engine, one or more indications of adiabetic foot condition. The method may further include checking theoptical image data one or more of image quality, lighting conditions, orbody positioning. The method may further include, prior to collectingthe physical touch sensitivity data, confirming the position of the footbased at least in part on the optical image data. The analysis enginemay include an image classifier.

In any of the described embodiments, a user interface may include aninteractive voice interface, a display, a visual indicator, acombination of such user interface features, or other user interfacefeatures.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing aspects and many of the attendant advantages of thisinvention will become more readily appreciated as the same become betterunderstood by reference to the following detailed description, whentaken in conjunction with the accompanying drawings, wherein:

FIG. 1 is a block diagram that depicts electronic systems that may beused in disclosed embodiments;

FIG. 2 is a flow chart that describes an illustrative weight-activateddata collection and analysis workflow that may be used in disclosureembodiments;

FIG. 3 is a flowchart of an illustrative monofilament exam workflow thatmay be used in disclosure embodiments;

FIG. 4 is a perspective view of a disclosed embodiment integrated in astanding scale;

FIG. 5 is a schematic diagram of a monofilament assembly that may beused in described embodiments for peripheral neuropathy testing; and

FIG. 6 is a block diagram that illustrates aspects of an illustrativecomputing device appropriate for use in accordance with embodiments ofthe present disclosure.

DETAILED DESCRIPTION

The present disclosure describes embodiments that facilitatenon-invasive detection of skin problems in the feet or other areas,including neuropathy, vascular disease, and ulcers, such as thoseassociated with diabetes mellitus.

In the following description, numerous specific details are set forth inorder to provide a thorough understanding of illustrative embodiments ofthe present disclosure. It will be apparent to one skilled in the art,however, that many embodiments of the present disclosure may bepracticed without some or all of the specific details. In someinstances, well-known process steps have not been described in detail inorder not to unnecessarily obscure various aspects of the presentdisclosure. Further, it will be appreciated that embodiments of thepresent disclosure may employ any combination of features describedherein. The illustrative examples provided herein are not intended to beexhaustive or to limit the claimed subject matter to the precise formsdisclosed.

Diabetic foot infection is the most common complication of diabetesmellitus leading to hospitalization and the most frequent cause ofnon-traumatic lower extremity amputation. Diabetic foot ulcers and otherfoot infections develop due to reduced feeling in the foot fromperipheral neuropathy, the most common form of diabetic neuropathy.People that suffer from such conditions may not be aware of abrasions orhotspots that may develop into ulcers, that wounds are not healing, orthat foreign objects have become lodged in the foot.

To address problems such as these, disclosed embodiments use acombination of sensors (e.g., optical and physical sensors) combinedwith related processing techniques (e.g., machine-learned classifiers)to help detect skin conditions (e.g., possible complications fromdiabetes). As described in detail below, the user or patient may beguided through operation of the device using an interactive voicesystem.

One possible sensing mechanism that may be used in disclosed embodimentsis a group of low-cost image sensors (e.g., in commercially availablecameras), capturing visible spectrum or near-IR images. In a disclosedembodiment, cameras are arranged in pairs (e.g., with one above and onebelow the subject body part being measured). Many-camera setups can alsobe used to enhance the camera coverage and increase the accuracy of theprediction algorithms. Single-camera applications are also possible,though in practice the user may need to reposition his body to get fullcamera coverage of the body part in question. The disclosed imagesensors and cameras may be used alone, or in combination with othersensing systems.

A second sensing mechanism that may be used in disclosed embodimentsuses a thermographic infrared image sensor (e.g., in commerciallyavailable infrared cameras) for detecting areas of varying skintemperature which can help identify regions that are eithercooler-than-surrounding areas (which may indicate conditions such ascompromised blood flow) or hotter-than-surrounding areas (which mayindicate conditions such as active infections). In a disclosedembodiment, the infrared image sensors (e.g., in one or more thermalcameras) are co-located with the visible-spectrum image sensors (e.g.,with one infrared camera above and one below the subject body part beingmeasured).

A third sensing mechanism that may be used in disclosed embodiments is aphysical sensor. In a disclosed embodiment, the physical sensor uses oneor more servo-actuated monofilaments to test for skin sensation loss. Amonofilament exam is a test used to identify cases of peripheralneuropathy in diabetic patients. This technique is similar in somerespects to the Semmes-Weinstein monofilament exam used by physicians,although the administration of the test, features of the testing device,and collection and analysis of the data are different than traditionaltests, as described in detail below.

In a disclosed embodiment, the device attaches a series of monofilamentfibers with a standard gauge (e.g., a 5.07 gauge fiber that produces 10g of pressure) to micro-servo actuators placed in locations distributedaround the device in order to contact test sites of the body part to bemeasured. On a foot, illustrative test site locations include the heel,foot arch, ball of the foot, behind the toes, and the big toe. The testmay be administered with an interactive user interface, such as aninteractive voice system. (As an alternative or in addition to theinteractive voice system, the user interface may be implemented as agraphical user interface (e.g., with a touch screen) or in some otherway.) The user interface may, for example, provide instructions to thepatient on how to start the test or prompt the patient (e.g., using arecorded or synthesized voice output) to say or otherwise indicate(e.g., with a button press, a gesture or other user input) when theyfeel a sensation from the monofilament. Responses from the patient canthen be processed, recorded, and acted upon by the system as describedherein.

Other physical sensing or testing mechanisms may be used in combinationwith or in place of monofilament tests. For example, the system mayinclude circuitry embedded in the foot platform to test the user'sability to feel heat or pain by means of integrated heating strips orlow-current electrical discharges. In such embodiments, a heat-testingdevice may use an optically transparent but electrically conductivematerial such as indium tin oxide to conduct current to the test sitewhere it is run through a higher-resistance portion of the coating inorder to generate resistive heating, similar to the way aircraft windowheaters work. As in other embodiments described herein, the user maythen be prompted (e.g., using a recorded or synthesized voice output) tosay or otherwise indicate (e.g., with a button press, a gesture or otheruser input) when they feel a sensation from the heating element. Theheat sensitivity testing method may include several different levels ofheating to test for sensation to obtain a more accurate assessment ofthe level of neuropathy present. An electrical discharge device may usetransparent conductive material to route a circuit to several test siteslocated around the foot (or other body part being tested). A small gapis left for the user's body to complete the circuit and introduceelectrical stimulation. This may be done with high-voltage, low-currentelectricity as is commonly used in other medical diagnostic equipment totest for pain responses. Again, the user is prompted to indicate whenthey feel the stimulus. The intensity of the discharge can be varied toobtain a more accurate assessment of the level of neuropathy present.

In a disclosed embodiment, the sensors and related structures andcontrol circuitry are combined and integrated into a standing scale formfactor. A standing scale (e.g., a bathroom scale) provides a surface onwhich a person may stand, which provides a suitable platform forfoot-based data collection. This disclosed embodiment also has thebenefit of collecting the user's weight, which is also an importantmetric for diabetic patients, since weight management is often animportant part of a diabetes management regimen.

FIG. 1 is a block diagram that depicts electronic systems that may beused in disclosed embodiments. In the example shown in FIG. 1,microcontroller 51 controls program execution and sensor integration,and is powered by a low voltage power supply 61, and uses a durablestorage device 62, such as a magnetic hard drive or static flash drive,for program and data storage. Alternatively, the device may becontrolled by some other controller or computing device.

FIG. 1 also depicts an illustrative user interface in the form of aninteractive voice system. The interactive voice system provides a userexperience which makes use of a speaker 11 to provide audio output andmicrophones with related speech recognition software or hardware tolisten for user commands and responses to questions. The interactivevoice system may use a single microphone or an array of microphones 12,which may be organized for beamforming for better background noiserejection. The illustrative user interface also uses a visual indicator,such as a multi-color cue light 13, to indicate various interfacestates. In this example, the cue light 13 may be used to indicate statessuch as microphone active, microphone muted, system busy (e.g., whencapturing an image or processing a captured image), and when the systemis speaking or providing other output.

During operation, the system may obtain data from one or more sensors,which may be physical or optical. In the example shown in FIG. 1, acollection of load cells 21, which may be arranged in groups of four,are used to measure the user's weight. The system may self-tare tosubtract the weight of other device equipment such as the footbed,electronics, and cameras. For example, the system may performself-taring during device initialization, before the first userweigh-in. Load cells may be connected to the microcontroller by way ofan analog-to-digital amplifier/converter such as the AVIA SemiconductorHX711.

In some embodiments, the device also includes an array of monofilamentprobe assemblies 22 that are used to test the user's foot for peripheralneuropathy. These are described in more detail in FIG. 3. The deviceuses optical image sensors (e.g., in the form of cameras) to createimages of the user's feet (or other body areas in some embodiments). Inthe example shown in FIG. 1, visible-light cameras 31 are used, alongwith other cameras that capture images at other wavelengths. In someembodiments, to reduce cost and complexity visible light cameras 31 maybe commercially available cameras with visible-light image sensors suchas those found in cellular phones. Other cameras may use image sensorscalibrated to capture visible light, near-infrared light, infraredlight, or some combination thereof. In some embodiments, wide-anglelenses may be used in conjunction with image sensors to enable morecompact chassis design, such as for cameras mounted below a footplatform. Near-infrared cameras 32 may be used to capture extendedspectrum information. Described embodiments may include one or moreillumination sources 34 (e.g., LED lights) that provide more consistentimage lighting for visible-light and/or near-infrared image sensors.Consistent image lighting can improve image classifier accuracy.

Some embodiments use thermal image sensors to capture heat data aboutthe user's body. In the example shown in FIG. 1, thermal image sensorsare included in thermal (far-infrared) cameras 33. Thermal imagingapplied to skin provides the ability to indicate areas of concern, suchas skin regions where the skin is cooler than surrounding skin, possiblyindicating lower-than-normal blood supply, which could indicate a likelyarea for the development of peripheral neuropathy. Alternately, a skinregion that is higher temperature than the surrounding skin may indicatethe development of an infection such as a diabetic foot ulcer.

In some embodiments, subsequent to collection of optical imaging data,the images are provided as input to image processing software, such as aneural network classifier pipeline 41, which then performs a series ofclassification steps related to diagnosis or treatment. Some exemplaryclassification steps include, for example, detecting the presence,position and orientation of feet (or other body parts); detecting thepresence and location of skin abnormalities (e.g., ulcers, foreignobjects, or abnormal temperatures); and classifying these abnormalities(e.g., as possible areas of peripheral neuropathy or infection). In eachof these steps, good results can be obtained by using a deepconvolutional neural network. Many existing commercial and open-sourceframeworks can be used for this task. Basic principles of trainingclassifiers are well known to those skilled in the art of machinelearning, and these basic principles need not be described here.

In described embodiments, training classifiers involves collectingextensive datasets of feet (or other body parts), both with and withoutskin abnormalities being searched for, manually labeling this data withthe correct classification labels for each step in the classificationpipeline (e.g., presence, position, orientation of feet, or presence andlocation of skin abnormalities, types of abnormalities). This data isthen used to train the machine-learned classifiers and iterativelyimprove the classifier accuracy by obtaining new data, adjusting thesteps in the classification pipeline, extracting new features to assistin classification, etc. The overall classifier pipeline prediction canbe measured with the precision of the predictions (e.g., the percentageof predictions that correctly find positive results) and the recall ofthe predictions (e.g., percentage of truly positive results that resultin positive predictions). These metrics can be balanced in order toobtain an acceptable tradeoff between the two.

The classification pipeline output may be multi-class; for example, itmay identify diabetic foot ulcers as well as other foot conditions suchas cuts, bruises, corns, warts, etc. The classification pipeline outputmay alternately output a binary classification indicating whether agiven skin issue requires further medical follow-up. The binaryclassification approach may be useful in situations where an abnormalityis detected to be present but, due to factors such as poor image qualityor missing images, the abnormality cannot be accurately classified.

Some embodiments send data (e.g., patient weight data, raw image data,image classification data) to other devices for storage or furtherprocessing. For example, data may be transmitted through a wirelessnetworking adapter 63 and then through a network 64 to arrive at aremote computer system, such as a patient data management service 65.This service may store weight data, raw images, classifier output, orother data and perform further image processing, test the data againstpredefined rules such as having positive classifier predictions orweight gains above some threshold, and communications such as patientfollow up messages. For example, in some embodiments a positiveclassification reading for foot ulcers may trigger a computer system(e.g., the patient data management service 65) to send an alert to thepatient or the patient's care team for follow-up, and send a report(e.g., including images) directly into the patient's electronic medicalrecords.

FIG. 4 is a perspective view of a disclosed embodiment integrated in astanding scale. In the example shown in FIG. 4, the device includes asuitably sized foot platform 401 for the user to stand on during use.(Although embodiments described herein refer to users standing on theplatform, it should be readily understood that in other embodiments thedevice can be modified, such as with a bench or chair, such that theuser is not required to stand.) The platform 401 may be constructed of astrong transparent material such as polycarbonate or tempered glass inorder to provide the ability for upward-facing cameras 410 to image thebottoms of the user's feet. The transparent material may be selectedbased on the imaging to be performed. For example, to allowthermographic cameras to capture images through the foot platform, asuitable material that is transparent to long-infrared wavelengths maybe used. Built-in illumination 411, such as LED lights, may be used toprovide consistent and sufficient lighting for the images. To captureimages of the user's feet at close range, the cameras 410 may includewide angle lenses, and may be arranged in an array. This design allowsthe platform 401 to be constructed with a low profile, which reduces thelikelihood of injury due to tripping or falling when using the device.In one embodiment, the footbed measures 12 inches×12 inches, and uses apair cameras with 150° field of view to obtain full coverage of thefootbed at a range of approximately 3.2 inches. In this example, theoptical distortion of these cameras is minimal enough to not require anyspecial processing, and give clear corner-to-corner resolution.

The platform 401 is supported by four load cells, which are in turnsupported by support legs 402. The load cells are used to measure theweight of the user. For mechanical simplicity and to prevent binding orfriction, which may produce inaccurate weight measurements, othercomponents on the device may be attached to the foot platform 401. Theweight of the foot platform and other components attached to it may betared by the device during an automatic taring process, which may beperformed during device power-up, device restart, or at some other time.

In some situations, imaging of the tops of the user's feet may bedesirable. For this type of imaging, image sensors may be included in anupper head assembly 404 attached to a support arm 403. The upper headassembly also may include elements of a user interface, which may bebeneficial for locating the user interface closer to the user's head toallow the user to more easily interact with the user interface (e.g., tomore easily detect the user's voice in a user interface with voicecontrol functionality). In the example shown in FIG. 4, the upper headassembly 404 includes a speaker 405 and a microphone 406 to supportvoice interactions with the user, as well as a visual indicator such asa multi-color cue light 407 to indicate interface states such asmicrophone active, microphone muted, system busy, system speaking (e.g.,providing synthesized or recorded voice output), or error conditions.Image sensors in the upper head assembly 404 may include cameras 408such as visible-light, near-infrared, and thermographic cameras, alongwith built-in illumination 409 in order to provide sufficient andconsistent lighting for the images.

As mentioned above, some embodiments are equipped with one or moremonofilament assemblies 412 to perform monofilament exams. Although onlyone monofilament assembly is shown in FIG. 4 for ease of illustration,the device may include several assemblies placed at various locationsaround the device in order to test different sites on the user's feet. Afoot outline (not shown) or other visual or tactile guide may beprovided on the foot platform 401 to assist users in positioning theirfeet correctly for imaging or monofilament testing.

FIG. 5 is a schematic diagram of a monofilament assembly that may beused in described embodiments for peripheral neuropathy testing. Indescribed embodiments, the test is derived from the Semmes-Weinsteinmonofilament exam used by physicians. During operation, an actuator(e.g., micro servo actuator 503) is activated to move the monofilament504 through an opening in the foot platform 502 so that the monofilament504 is in contact with the user's foot 501. Various forms of actuationare contemplated, including a rotary servo with an arm that is connectedto the monofilament, or a linear actuator. As shown in FIG. 5, theactuation occurs with sufficient force to cause the monofilament to bendor buckle below the foot platform 501. The device can be designed toensure that a consistent amount of pressure is applied during testing.In at least one embodiment, the monofilament is pre-calibrated to astandard amount of buckling force, e.g., 10 grams.

FIG. 2 is a flow chart that describes an illustrative weight-activateddata collection and analysis workflow in a disclosed embodiment. In theexample shown in FIG. 2, when a user steps onto the foot platform atstep 201, the device is activated. The device collects the weight overthe course of a trigger period (e.g., a few seconds) and compares thisto its trigger threshold weight (e.g., 10 pounds) and trigger period(e.g., one second) at step 202. If the measured weight is below thethreshold weight, or the weight is present for less than the triggerperiod, the activation is assumed to be accidental at step 203, and theworkflow ends. Other embodiments may use different thresholds for weightand trigger periods, or such thresholds may be omitted if not deemednecessary for a particular application.

In the example shown in FIG. 2, if the threshold weight is measured forthe trigger period, the user will be prompted (e.g., with synthesized orrecorded voice output from the speaker 11) to stand still at step 204,since imaging can take a few seconds and remaining motionless during theimage capture process may help the system to obtain higher qualityimages. The device can then, concurrently or in series, use load cellsat step 205 to measure the user's weight, use visual light and/ornear-infrared image sensors to capture images of the user's feet at step206, and use infrared imaging sensors to obtain thermographic images ofthe user's feet at step 207. Data obtained in steps 205, 206, and 207can then be tested in step 209 using a classifier or other imageanalysis or pattern recognition techniques.

With regard to images, the system can use techniques such as edgedetection to ensure that quality, lighting, and body positioning aresatisfactory for input into the image classification pipeline. Forexample, if image analysis indicates blurry edges in locations whereclear edges are expected, or if one foot is detected when two feet areexpected, the system may infer that the user was not standing still ornot positioned correctly during the image capture. The determination asto whether the input data are satisfactory may vary depending onimplementation. If the inputs are found to be deficient, the userinterface may prompt the user to take corrective action at step 210. Forexample, if one of the user's feet was not positioned for a clear viewfrom the camera, the user interface may prompt the user to move thatfoot back onto the foot platform. After suggesting corrective action,the device then attempts to obtain new sensor inputs and returns to step204. If satisfactory sensor data cannot be obtained (e.g., after athreshold number of collection attempts), the user interface may promptthe user to try again later at step 211 and end the workflow.

Once satisfactory sensor inputs are obtained, the inputs are processedfurther. For example, images may be passed to a neural networkclassifier pipeline that classifies the images at step 212. Afterclassification—which may indicate the presence or absence of conditionslike diabetic foot ulcers—the system may upload data such asclassification results, raw images, and the user's weight to a patientdata management service at step 213. While some embodiments may uploaddata, such as the sensor and classification data, to other computingdevices, this is not required. For example, standalone devices that donot use a network connection or a patient data management service arecontemplated. In other scenarios, such as cloud computing arrangements,the system may omit local classification or image analysis and transmitonly raw images, or images and weight data, to an external system orserver that performs more intensive processing, such as image analysisand classification.

Referring again to the example shown in FIG. 2, after classification hasoccurred, the user interface provides the user with a summary of theprocess so far at step 214, which may include measurements andclassification outputs. The system may provide, for example, the user'sweight, how measurements such as weight may be trending compared withprevious measurements, and an assessment of whether any problematicissues were detected.

In some embodiments or usage scenarios, the summary provided to the userat step 214 will mark the end of the workflow. In other embodiments orscenarios, the workflow may proceed with further examination of theuser. In the example shown in FIG. 2, in embodiments equipped withmonofilament probes, the system will check if it is time to perform amonofilament examination at step 215. This check could be based on ascheduled examination period, or it could be a rule-based action basedon results observed from the previous steps in the exam. For example, ifa thermographic camera detects hot or cold spots (skin regions that arecooler or warmer than surrounding regions), these conditions could becross-verified with a physical monofilament exam. If the monofilamentexamination is to be performed, the system initiates the monofilamentexam process at step 216. If the device is not equipped with amonofilament examination device, or if it is not time for a monofilamentexam, the user interface concludes the measurement session by remindingthe user of any important information that may be pertinent at step 217.For example, this might include the date of their next monofilamentexam, or if the user is following a larger care plan, it may includeother aspects of disease management like tips for healthy eating,reminders to exercise, and so on. The workflow then ends.

Many alternatives to the workflow of FIG. 2 are possible. For example,the system may omit providing a summary of the procedure, or the systemmay provide the summary at some other time or in some other way. Forexample, if the device is located in a public area such as a pharmacy,the device may provider the user with the option to receive an email orother communication indicating results of the test for privacy reasons,rather than providing them as audible voice output to the user.

FIG. 3 is a flowchart of an illustrative monofilament exam workflow. Insome embodiments, the monofilament exam is initiated while a user isstanding on the device, as part of a weight-activated workflow, such asthe workflow illustrated in

FIG. 2. The user interface prompts the user to stand still at step 301,since the monofilament exam may take a couple of minutes or more tocomplete. The user interface may provide an indicator, such as a visualcountdown timer or feedback from the cue light, to indicate that theexam is in progress or estimated time remaining. The device selects testsites for monofilament tests at step 302. In this example, the deviceselects a random order for the test sites where monofilament tests willbe actuated, and may also include one or more placebo measurements.Alternatively, the device may perform the exam according to apredetermined order of test sites or placebo measurements, or selectfrom among a set of possible orders of test sites or placebomeasurements.

The device then uses the imaging system in combination with furtherprocessing (e.g., a classifier or other image analysis algorithm such asedge detection) to check if the user's feet are in a proper position atstep 303. If the feet are out of position at step 304, the userinterface prompts the user to take corrective action at step 305. Oncethe user's feet are properly positioned, the system determines whetherthe first test site is a placebo measurement at step 306. If the actionperformed at the site is a non-placebo measurement, the relevantmonofilament test assembly for that test site is actuated at step 307.If the action performed at the test site is a placebo measurement, amonofilament probe assembly that does not contact the user's foot willbe actuated at step 308. Placebo tests may be used to test forfalse-positive responses by the user. Since the monofilament examactuators may generate a certain amount of noise and vibration during anactual exam, in a placebo test it may be important to actually perform aphysical actuation to simulate the noise and vibration of a real examand accurately test for false-positive response.

Following either the placebo measurement or the actual exam at the testsite, the user interface prompts the user to indicate if they felt thelast touch at step 309. The user can then respond with an affirmative ornegative response at step 310, which the system will match against thetest that was actually performed. At step 311, the system determineswhether there are more sites to be tested or placebo measurements to beperformed. If so, steps 303-310 may be repeated for subsequent testsites or placebo measurements in the set selected at step 302. Once allsites have been tested and any placebo measurements have been performed,the results, including which test sites were actuated and how the userresponded, may be uploaded to a patient data management service at step312. Some embodiments may use the device as a standalone device withoutthe use of a patient data management service, in which case this stepmay be skipped. The user interface summarizes the results for the userat step 313. This summary may include listing how many sites weretested, how many the user was able to correctly identify, and a list ofany test sites where the user did not feel a real actuation.

Many alternatives to the workflow of FIG. 3 are possible. For example,the system may omit providing a summary of the procedure, or the systemmay provide the summary at some other time or in some other way. Forexample, if the device is located in a public area such as a pharmacy,the device may provider the user with the option to receive an email orother communication indicating results of the test for privacy reasons,rather than providing them as audible voice output to the user.

Illustrative Computing Devices and Operating Environments

Unless otherwise specified in the context of specific examples,computing techniques and related tools described herein may beimplemented by any suitable computing device or set of devices.

In any of the described examples, an engine may be used to performactions. An engine includes logic (e.g., in the form of computer programcode) configured to cause one or more computing devices to performactions described herein as being associated with the engine. Forexample, a computing device can be specifically programmed to performthe actions by having installed therein a tangible computer-readablemedium having computer-executable instructions stored thereon that, whenexecuted by one or more processors of the computing device, cause thecomputing device to perform the actions. The particular enginesdescribed herein are included for ease of discussion, but manyalternatives are possible. For example, actions described herein asassociated with two or more engines on multiple devices may be performedby a single engine. As another example, actions described herein asassociated with a single engine may be performed by two or more engineson the same device or on multiple devices.

Some of the functionality described herein may be implemented in thecontext of a client-server relationship. In this context, server devicesmay include suitable computing devices configured to provide informationand/or services described herein. Server devices may include anysuitable computing devices, such as dedicated server devices. Serverfunctionality provided by server devices may, in some cases, be providedby software (e.g., virtualized computing instances or applicationobjects) executing on a computing device that is not a dedicated serverdevice. The term “client” can be used to refer to a computing devicethat obtains information and/or accesses services provided by a serverover a communication link. However, the designation of a particulardevice as a client device does not necessarily require the presence of aserver. At various times, a single device may act as a server, a client,or both a server and a client, depending on context and configuration.Actual physical locations of clients and servers are not necessarilyimportant, but the locations can be described as “local” for a clientand “remote” for a server to illustrate a common usage scenario in whicha client is receiving information provided by a server at a remotelocation. Alternatively, a peer-to-peer arrangement, or other models,can be used.

FIG. 6 is a block diagram that illustrates aspects of an illustrativecomputing device 600 appropriate for use in accordance with embodimentsof the present disclosure. The description below is applicable toservers, personal computers, mobile phones, smart phones, tabletcomputers, embedded computing devices, and other currently available oryet-to-be-developed devices that may be used in accordance withembodiments of the present disclosure.

In its most basic configuration, the computing device 600 includes atleast one processor 602 and a system memory 604 connected by acommunication bus 606. Depending on the exact configuration and type ofdevice, the system memory 604 may be volatile or nonvolatile memory,such as read only memory (“ROM”), random access memory (“RAM”), EEPROM,flash memory, or other memory technology. Those of ordinary skill in theart and others will recognize that system memory 604 typically storesdata and/or program modules that are immediately accessible to and/orcurrently being operated on by the processor 602. In this regard, theprocessor 602 may serve as a computational center of the computingdevice 600 by supporting the execution of instructions.

As further illustrated in FIG. 6, the computing device 600 may include anetwork interface 610 comprising one or more components forcommunicating with other devices over a network. Embodiments of thepresent disclosure may access basic services that utilize the networkinterface 610 to perform communications using common network protocols.The network interface 610 may also include a wireless network interfaceconfigured to communicate via one or more wireless communicationprotocols, such as WiFi, 2G, 3G, 4G, LTE, WiMAX, Bluetooth, and/or thelike.

In FIG. 6, the computing device 600 also includes a storage medium 608.However, services may be accessed using a computing device that does notinclude means for persisting data to a local storage medium. Therefore,the storage medium 608 depicted in FIG. 6 is optional. In any event, thestorage medium 608 may be volatile or nonvolatile, removable ornonremovable, implemented using any technology capable of storinginformation such as, but not limited to, a hard drive, solid statedrive,

CD-ROM, DVD, or other disk storage, magnetic tape, magnetic diskstorage, and/or the like.

As used herein, the term “computer-readable medium” includes volatileand nonvolatile and removable and nonremovable media implemented in anymethod or technology capable of storing information, such ascomputer-readable instructions, data structures, program modules, orother data. In this regard, the system memory 604 and storage medium 608depicted in FIG. 6 are examples of computer-readable media.

For ease of illustration and because it is not important for anunderstanding of the claimed subject matter, FIG. 6 does not show someof the typical components of many computing devices. In this regard, thecomputing device 600 may include input devices, such as a keyboard,keypad, mouse, trackball, microphone, video camera, touchpad,touchscreen, electronic pen, stylus, and/or the like. Such input devicesmay be coupled to the computing device 600 by wired or wirelessconnections including RF, infrared, serial, parallel, Bluetooth, USB, orother suitable connection protocols using wireless or physicalconnections.

In any of the described examples, input data can be captured by inputdevices and processed, transmitted, or stored (e.g., for futureprocessing). The processing may include encoding data streams, which canbe subsequently decoded for presentation by output devices. Media datacan be captured by multimedia input devices and stored by saving mediadata streams as files on a computer-readable storage medium (e.g., inmemory or persistent storage on a client device, server, administratordevice, or some other device). Input devices can be separate from andcommunicatively coupled to computing device 600 (e.g., a client device),or can be integral components of the computing device 600. In someembodiments, multiple input devices may be combined into a single,multifunction input device (e.g., a video camera with an integratedmicrophone). The computing device 600 may also include output devicessuch as a display, speakers, printer, etc. The output devices mayinclude video output devices such as a display or touchscreen. Theoutput devices also may include audio output devices such as externalspeakers or earphones. The output devices can be separate from andcommunicatively coupled to the computing device 600, or can be integralcomponents of the computing device 600. Input functionality and outputfunctionality may be integrated into the same input/output device (e.g.,a touchscreen). Any suitable input device, output device, or combinedinput/output device either currently known or developed in the futuremay be used with described systems.

In general, functionality of computing devices described herein may beimplemented in computing logic embodied in hardware or softwareinstructions, which can be written in a programming language, such as C,C++, COBOL, JAVA™, PHP, Perl, Python, Ruby, HTML, CSS, JavaScript,VBScript, ASPX, Microsoft .NET™ languages such as C#, and/or the like.Computing logic may be compiled into executable programs or written ininterpreted programming languages. Generally, functionality describedherein can be implemented as logic modules that can be duplicated toprovide greater processing capability, merged with other modules, ordivided into sub-modules. The computing logic can be stored in any typeof computer-readable medium (e.g., a non-transitory medium such as amemory or storage medium) or computer storage device and be stored onand executed by one or more general-purpose or special-purposeprocessors, thus creating a special-purpose computing device configuredto provide functionality described herein.

Extensions and Alternatives

Many alternatives to the systems and devices described herein arepossible. For example, individual modules or subsystems can be separatedinto additional modules or subsystems or combined into fewer modules orsubsystems. As another example, modules or subsystems can be omitted orsupplemented with other modules or subsystems. As another example,functions that are indicated as being performed by a particular device,module, or subsystem may instead be performed by one or more otherdevices, modules, or subsystems. Although some examples in the presentdisclosure include descriptions of devices comprising specific hardwarecomponents in specific arrangements, techniques and tools describedherein can be modified to accommodate different hardware components,combinations, or arrangements. Further, although some examples in thepresent disclosure include descriptions of specific usage scenarios,techniques and tools described herein can be modified to accommodatedifferent usage scenarios. Functionality that is described as beingimplemented in software can instead be implemented in hardware, or viceversa.

Many alternatives to the techniques described herein are possible. Forexample, processing stages in the various techniques can be separatedinto additional stages or combined into fewer stages. As anotherexample, processing stages in the various techniques can be omitted orsupplemented with other techniques or processing stages. As anotherexample, processing stages that are described as occurring in aparticular order can instead occur in a different order. As anotherexample, processing stages that are described as being performed in aseries of steps may instead be handled in a parallel fashion, withmultiple modules or software processes concurrently handling one or moreof the illustrated processing stages. As another example, processingstages that are indicated as being performed by a particular device ormodule may instead be performed by one or more other devices or modules.

While illustrative embodiments have been illustrated and described, itwill be appreciated that various changes can be made therein withoutdeparting from the spirit and scope of the invention.

1. A method for automated diagnosis of a diabetic foot condition, themethod comprising: capturing, by one or more image capture devices of amedical diagnostic apparatus, optical image data of a target area of afoot; collecting, by a touch sensitivity testing device of the medicaldiagnostic apparatus, physical touch sensitivity data for the targetarea of the foot; transmitting, by the medical diagnostic apparatus, theoptical image data, the physical touch sensitivity data, or acombination of such data to an analysis engine; and outputting, by theanalysis engine, one or more indications of a diabetic foot condition.2. The method of claim 1 further comprising checking the optical imagedata for one or more of image quality, lighting conditions, or bodypositioning.
 3. The method of claim 1 further comprising, prior tocollecting the physical touch sensitivity data, confirming the positionof the foot based at least in part on the optical image data.
 4. Themethod of claim 1, wherein the touch sensitivity testing devicecomprises a servo-actuated monofilament probe.
 5. The method of claim 1,wherein the analysis engine comprises an image classifier.
 6. Anon-transitory computer-readable medium having stored thereininstructions configured to cause one or more computing devices to causesteps to be performed for automated diagnosis of a diabetic footcondition, the steps comprising: capturing, by one or more image capturedevices of a medical diagnostic apparatus, optical image data of atarget area of a foot; collecting, by a touch sensitivity testing deviceof the medical diagnostic apparatus, physical touch sensitivity data forthe target area of the foot; transmitting, by the medical diagnosticapparatus, the optical image data, the physical touch sensitivity data,or a combination of such data to an analysis engine; and outputting, bythe analysis engine, one or more indications of a diabetic footcondition.
 7. The non-transitory computer-readable medium of claim 6,the steps further comprising checking the optical image data for one ormore of image quality, lighting conditions, or body positioning.
 8. Thenon-transitory computer-readable medium of claim 6, the steps furthercomprising, prior to collecting the physical touch sensitivity data,confirming the position of the foot based at least in part on theoptical image data.
 9. The non-transitory computer-readable medium ofclaim 6, wherein the touch sensitivity testing device comprises aservo-actuated monofilament probe.
 10. The non-transitorycomputer-readable medium of claim 6, wherein the analysis enginecomprises an image classifier.
 11. A computer system comprising one ormore computing devices programmed to perform steps for automateddiagnosis of a diabetic foot condition, the steps comprising: causingone or more image capture devices of a medical diagnostic apparatus tocapture optical image data of a target area of a foot; causing a touchsensitivity testing device of the medical diagnostic apparatus tocollect physical touch sensitivity data for the target area of the foot;causing the medical diagnostic apparatus to transmit the optical imagedata, the physical touch sensitivity data, or a combination of such datato an analysis engine; and obtaining one or more indications of adiabetic foot condition from the analysis engine.
 12. The computersystem of claim 11, the steps further comprising checking the opticalimage data for one or more of image quality, lighting conditions, orbody positioning.
 13. The computer system of claim 11, the steps furthercomprising, prior to collecting the physical touch sensitivity data,confirming the position of the foot based at least in part on theoptical image data.
 14. The computer system of claim 11, wherein thetouch sensitivity testing device comprises a servo-actuated monofilamentprobe.
 15. The computer system of claim 11, wherein the analysis enginecomprises an image classifier.